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on glacier behaviour, including extreme events. For this work you should be familiar with image (pre-)processing techniques to obtain high quality quantitative data from time lapse imagery. This may include
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unique opportunity to contribute to a pioneering platform that could transform process-scale chemistry in the pharmaceutical and agrochemical industry, combining hands-on engineering with cutting-edge
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readiness. This is a unique opportunity to contribute to a pioneering platform that could transform process-scale chemistry in the pharmaceutical and agrochemical industry, combining hands-on engineering with
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novel plasma-disturbance sensing techniques. The role sits within the Department of Electrical Engineering and Electronics, part of the Faculty of Science and Engineering, which has a strong track record
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as possible thereafter. The Role Drawing on over a decade of formulation data, you will develop machine learning models that link chemical composition and processing parameters to the physical and
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials
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cellular biology approaches. - Analyse tumour samples from pre-clinical models and patient cohorts using high-dimensional platforms, including multiplex imaging, flow and mass cytometry
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We are seeking to appoint a postdoctoral researcher to join our programme on application-specific detector R&D for physics experiments, supported by the UK Science and Technology Facilities Council
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processes and milestones including experience with research design, ethics and governance. Experience working in one or more of the following: clinical trials, experience-sampling methods, health technology
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nature of the role, prior experience in working with rheodialysis technique is an essential requirement. The position will be hosted in the Department of Materials, Design and Manufacturing Engineering at